bp/Big_Data_Assignment_2
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random centres

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This commit is contained in:
Joe Darby
2016-12-17 18:01:30 +00:00
parent 6d1d5858e1
commit 7245521a78
2 changed files with 42 additions and 14 deletions
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.idea/workspace.xml
Generated
+32 -9
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@@ -2,9 +2,6 @@
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<change type="MODIFICATION" beforePath="$PROJECT_DIR$/src/main/scala/KMeans.scala" afterPath="$PROJECT_DIR$/src/main/scala/KMeans.scala" />
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<ignored path="$PROJECT_DIR$/target/" />
@@ -24,8 +21,8 @@
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@@ -43,6 +40,16 @@
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@@ -238,12 +245,12 @@
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@@ -313,10 +320,26 @@
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<entry file="jar://$MAVEN_REPOSITORY$/org/apache/spark/spark-core_2.10/1.6.0/spark-core_2.10-1.6.0-sources.jar!/org/apache/spark/rdd/RDD.scala">
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src/main/scala/KMeans.scala
+10 -5
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@@ -17,8 +17,8 @@ object KMeans {
val rows = relevantData.rdd
//val rowsAsArray = rows.map(row => List(row.getInt(0).toFloat, row.getInt(1).toFloat, row.getInt(2).toFloat) )
val rowsAsArray = rows.map(row => row.getInt(0).toFloat)
val maximum = rowsAsArray.reduce((a, b) => math.max(a, b))
println(maximum)
//val maximum = rowsAsArray.reduce((a, b) => math.max(a, b))
//println(maximum)
//rowsAsArray.foreach(println)
val K = 4
//number of intended clusters
@@ -26,19 +26,24 @@ object KMeans {
val m = 1 //number of features
//var centres = new ArrayBuffer[Float]()
//var centres: Array[Float] = rowsAsArray.takeSample(false, K, System.nanoTime().toInt)
var centres: Array[Float] = rowsAsArray.takeSample(false, K, System.nanoTime().toInt)
//To reduce chance of two random centres being the same, add i to each
for (i <- 0 until K) {
centres(i) += i
}
/*var centres : ArrayBuffer[Float] = new ArrayBuffer[Float](K)
for (i <- 0 until K) {
centres(i) = randomCentres(i)
}*/
var centres = new Array[Float](K)
/*var centres = new Array[Float](K)
val someNumber = maximum / K
for (i <- 0 until K) {
centres(i) = someNumber * i
}
}*/
for (i <- 0 until iterations) {
centres = clustering(centres, rowsAsArray, m, K)